Natural Language processing library for Macedonian (MK)

nlmk is a small library for nlp specialized for Macedonian language, focusing on localization of the tokenizer and the stopwords and it also provides document analysis. People familiar with nltk (python) can be introduced painlessly. It also has focus on working with large files (texts).

Requirements

nlmk requires the following third party libraries:

- ``pyparsing-1.5.7``

nlmk can also run with pypy. Please be careful to install the correct pyparsing version.

Fetch sentences

Display part of text, specified as a sentence-slice.

Examples: ::

python run.py sentences corpus/racin.txt 7
python run.py sentences corpus/racin.txt :2
python run.py sentences corpus/racin.txt 3:10
python run.py sentences corpus/racin.txt 80:

Concordance

Display a word occuring in a fixed-length window (default: 9).

Examples: ::

python run.py concordance corpus/racin.txt филозофија
python run.py concordance corpus/racin.txt филозофија 2

N-gram extraction from texts

Use the nlmk.ngramgen module, or call it through the run.py caller.

Example: ::

python run.py ngramgen corpus/racin.txt 10 2 1

This will generate unigrams, bigrams and trigrams:

- the unigrams (words) show up at least 10 times
- the bigrams occur at least 2 times
- the trigrams occur at least 1 time (all trigrams)

POS-tagers

Use the nlmk.tagger module, or call it through the run.py caller.

Example:

First you need to build a tagger using one or more documents. This will build a tagger called sociology: ::

python run.py build-tagger sociology corpus/obezvrednuvanje.na.trudot.txt corpus/rabotni.sporovi.txt

This tagger can be used to tag some other documents: ::

python run.py tag corpus/racin.txt sociology

Term frequency

Use nlmk.corpus module, or call it through the run.py caller.

Example:

This will give the term frequency distribution: ::

python run.py tf corpus/racin.txt